Mortality Analysis of the Coronavirus nCoV-19 in India and 6 of its neighbouring countries

Hi Readers! As we know it very well how gloomy these days are due to the outbreak of the disastrous disease which is acting relentlessly as a time-bomb against the survival of humanity. Before starting our mortality study, let us know some preliminary facts ranging from its origin & history to transmission.

Origin & History

The city of Wuhan, Hubei province, China, was the origin of a severe pneumonia outbreak in December 2019, attributed to a novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS‐CoV‐2]). The international Committee on Taxonomy of viruses renamed the novel coronavirus (ie, previously 2019‐nCoV) responsible for the current outbreak, as severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). The structure of the Coronavirus can be seen in the following picture.

If observed carefully, the crownlike protein spikes around the figure can be seen. Thus, for these crownlike protein spikes its name arose as Corona which means Crown. The microscopic picture was taken from The University of Hong Kong. The disease that has been creating a havoc all around the world is the so called coronavirus disease (COVID-19) and the virus responsible for this disease is severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). The World Health Organization on 11 March, 2020 declared this disease as "Pandemic". Of note, the Coronaviridae family includes the ongoing SARS‐CoV‐2, along with SARS‐CoV, Middle East respiratory syndrome coronavirus (MERS‐CoV), and common cold viruses (e.g, 229E, OC43, NL63, and HKU1).

Transmission

Coronaviruses are known to circulate in mammals and birds. Some studies revealed that both SARS‐CoV and MERS‐CoV are zoonotic in origin, originally coming from bats with SARS‐CoV spreading from bats to palm civets to humans, and MERS‐CoV spreading from bats to camels to humans. Recent research has also reported that the SARS‐CoV‐2 virus likely originated in bats. However, like SARS‐CoV, MERS‐CoV, and other coronaviruses, the SARS‐CoV‐2 virus may have been transmitted to humans by an intermediate animal host. Therefore, the identity of the animal source of SARS‐CoV‐2 remains a key and urgent question. The two researchers from China named Shen Yongyi and Xiao Lihua identified the pangolin as a potential source of the SARS‐CoV‐2 virus based on genetic comparison of coronaviruses taken from pangolins and from humans infected during the recent outbreak. They found the genome sequence of an isolated virus strain was 99% similar to that of the SARS‐CoV‐2 virus. Some have stated the virus is an outcome of the "Natural Selection". Thus, whether pangolins acted as a direct intermediate animal host of the SARS‐CoV‐2 virus or evolved through a natural selection is worth further investigation.

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In this blog, I would study the mortality rates and the daily confirmed cases of 6 bordering countries along with India. The data are collected from the John Hopkins University. The same data can also be loaded directly from GitHub. The graphs are drawn using R. Analyses were done on 29 March 2020. So data were accurate and up to date till 28 March, 2020. Rigorous study has been done from various research papers and from various other reliable and official sources. To start with, let us have a quick look the case fatality ratio pattern and its confidence interval for the countries in the table 1. The case fatality ratio is calculated using the following relation.

Wondering why CFR ? Because in this case, we are interested to calculate the mortality rate independently of time. Moreover, CFR is a good choice when we are calculating the mortality in case of infectious disease.

N.B: While deriving the 95% Confidence Interval, continuity correction of 0.5 in studies with zero cell frequencies have been done.

From the table we see Case Fatality ratio vary significantly between countries which suggests considerable uncertainty over the exact case fatality rates/ratio. Bangladesh marks the highest. The next is India. CFRs for Nepal, Bhutan & Myanmar came out zeros as these countries have not accounted any death so far. However, there are various factors which are affecting these rates/ratios and thus are not comparable.The number of cases detected by testing will vary considerably by country and so as the CFR. Subjective bias which means those with severe disease are preferentially diagnosed can be cause of underestimation of the CFR. There may be delays between symptoms onset and deaths which can also lead to underestimation of the CFR. There may be factors that account for increased death rates in Bangladesh and India such as co-infection, inadequate healthcare, patients infected. There may be differences in how deaths are attributed to Coronavirus-dying with the disease (association) or dying from the disease (causation). These data (association or causation cases) are all together mingled into a one variable named: Deaths. This may have either underestimated the CFR or overestimated it. The CFRs for different countries are shown in the following figure.

Let us now look at the daily pattern of the confirmed cases in the following figure for the above mentioned countries. The data for such figure is loaded from here.

From the table 1 and the second figure of this blog, we see the mortality rate is high for Bangladesh whereas in the figure above, the number of infections is high for Pakistan. From the above graph we see the steep increase in the number of confirmed cases in Pakistan, followed by India. The majority of people who are infected most likely have not been tested, are not showing symptoms, and have been newly infected. This exponential growth can be saturate, stemmed, suppressed, or stopped entirely through a number of actions we take, both as individuals and as a collective society and they will have different effects and impacts on its growth. For instance, if we avoid large gatherings and keep a significant distance between ourselves and others' bodies, we can reduce the transmission rate. Moreover, equipped medical diagnostic, research & development, use of modern technology for surveillance highly the need of the hour. Interventions such as these can effectively slow down the rate of infection in the uninfected population significantly. This didn't happen in countries like Italy, Iran and the U.S during a critical period. So, it is expected from the countries analysed here to obtain such interventions prima-facie to prevent the infection rates and death rates from increasing further.

Thanks for Reading :)